Productivity estimation of bulldozers using generalized linear mixed models

Rashidi, Abbas; Nejad, H. Rashidi; Maghiar, Marcel

doi:10.1007/s12205-014-0354-0

Cited by 47 publications

(18 citation statements)

References 18 publications

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“…Therefore, the crawler-type dozer is often used in project site. It is worth mentioning that Rashidi et al [23] and Ok and Sinha [26] studied dozers to provide their proposed estimation models. To this end, the focus of this study is on the crawler-type dozer machine.…”

Section: Objectivesmentioning

confidence: 99%

“…Caterpillar believes to control more than half of the U.S. construction equipment market and one third of the world market [31]. Komatsu dozers are also typically employed in many earthmoving operation [23]. The machine models considered for this study are as follow:…”

Section: Machine Selectionmentioning

confidence: 99%

“…In particular, a comparison between the collected actual data and found nominal data could address the first sub-objective. In addition to the dozing distance, working condition, ground slope (i.e., grade%), and materials (i.e., soil) conditions have critical effects on dozer production [3,10,21,22,23,34]. Indeed, these three independent parameters are the main parameters critically play important roles to estimate dozer actual hourly production.…”

Section: Actual Productionmentioning

confidence: 99%

“…In addition, various related computer software has been developed and proposed to help project managers make decisions about construction machinery. In particular, the success of such research work and software is highly depends on machinery actual production [9,11,[23][24][25][26]. Rafsanjani et al [10] discussed that the nominal to actual hourly production could get a ratio of less than 0.3 in a project site.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, the model could not be extended in-practice to all models of machines working in various project sites. Recently, Rashidi et al [23] used a linear mixed model to estimate productivity of a model of dozer. They presented factors affect machine productions.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

A Statistical-based Approach to Evaluate the Production of Crawler-type Dozer in Construction Projects

Rafsanjani¹,

Gholipour²,

Xue³

2018

AJCEA

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Estimating the actual production rate of construction machinery which clearly differs from nominal production provided by machinery manufacturers always is a critical challenge in construction projects execution. Studies indicate that true estimation of actual production is a key element in estimating the time and cost required to terminate construction operations. However, current literature shows that it is still a quite challenging to estimate actual production. In particular, there are various independent parameters that affect the actual production rate. Understanding the role and importance of each parameter could lead to an accurate estimation for production rates. To this end, this paper presents a statistical-based approach to find the discrepancies between the nominal and actual production rates of crawler-type dozers and to understand how various parameters could affects the actual production rates. The data for the actual production of machine were records from productivity measurement of 39 dozers. Working condition, type of materials, and ground slope are three main independent parameters considered and evaluated for each machine. The results obtained from statistical analyses on the data and a comparison between these results with the data provided by Caterpillar and Komatsu manufacturers show a) the discrepancies between the actual and nominal hourly production, b) the effect of individual parameters on actual production, and c) the relationship between machinery working age and discrepancies. The findings of this study could be a unique help for project managers in planning of machinery and equipment in a project site.

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Section: Objectivesmentioning

confidence: 99%

Section: Machine Selectionmentioning

confidence: 99%